Source code for WORC.processing.ExtractNLargestBlobsn
#!/usr/bin/env python
# Copyright 2016-2021 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from skimage.measure import label, regionprops
import numpy as np
[docs]def ExtractNLargestBlobsn(binaryImage, numberToExtract=1):
"""Extract N largest blobs from binary image.
Arguments:
binaryImage: boolean numpy array one or several contours.
numberToExtract: number of blobs to extract (integer).
Returns:
binaryImage: boolean numpy are containing only the N
extracted blobs.
"""
# Get all the blob properties.
connectivity = binaryImage.ndim
if connectivity == 3 and binaryImage.shape[2] == 1:
# Oh no! Its a 2D image disguised as a 3D image! We must change connectivity to 2
connectivity = 2
labeledImage = label(binaryImage, connectivity=connectivity)
blobMeasurements = regionprops(labeledImage)
if len(blobMeasurements) == 1:
# Single blob, return input
binaryImage = binaryImage
else:
# Get all the areas
allAreas = list()
allCoords = list()
for blob in blobMeasurements:
allAreas.append(blob.area)
allCoords.append(blob.coords)
allAreas = np.asarray(allAreas)
if numberToExtract > 0:
# For positive numbers, sort in order of largest to smallest.
# Sort them.
indices = np.argsort(-allAreas)
elif numberToExtract < 0:
# For negative numbers, sort in order of smallest to largest.
# Sort them.
indices = np.argsort(allAreas)
else:
raise ValueError("Number of blobs to extract should not be zero!")
binaryImage = np.zeros(binaryImage.shape)
# NOTE: There must be a more efficient way to do this
for nblob in range(0, numberToExtract):
nblob = abs(nblob)
coords = allCoords[indices[nblob]]
for coord in coords:
if len(binaryImage.shape) == 2:
binaryImage[coord[0], coord[1]] = 1
else:
binaryImage[coord[0], coord[1], coord[2]] = 1
return binaryImage